code: def testDotProductAttention(
      self, batch, heads, length_q, length_kv, depth_k, depth_v
  ):
      query = tf.random_normal([batch, heads, length_q, depth_k])
      key = tf.random_normal([batch, heads, length_kv, depth_k])
      value = tf.random_normal([batch, heads, length_kv, depth_v])
  
      graph = mtf.Graph()
      mesh = mtf.Mesh(graph, "my_mesh")
      batch_dim = mtf.Dimension("batch", batch)
      heads_dim = mtf.Dimension("heads", heads)
      length_q_dim = mtf.Dimension("length_q", length_q)
      length_kv_dim = mtf.Dimension("length_kv", length_kv)
      depth_k_dim = mtf.Dimension("depth_k", depth_k)
      depth_v_dim = mtf.Dimension("depth_v", depth_v)
  
      mtf_query = mtf.import_tf_tensor(
          mesh,
          query,
          shape=mtf.Shape(
              [batch_dim, heads_dim, length_q_dim, depth_k_dim]
          ),
      )
      mtf_key = mtf.import_tf_tensor(
          mesh,
          key,
          shape=mtf.Shape(
              [batch_dim, heads_dim, length_kv_dim, depth_k_dim]
          ),
      )
      mtf_value = mtf.import_tf_tensor(
          mesh,
          value,
          shape=mtf.Shape(
              [batch_dim, heads_dim, length_kv_dim, depth_v_dim]
          ),
      )
      mtf_outputs = mtf.layers.dot_product_attention(
          mtf_query, mtf_key, mtf_value, mask=None, is_training=False
      )
      mesh_impl = mtf.placement_mesh_impl.PlacementMeshImpl(
          shape=[], layout={}, devices=[""]
      )
      lowering = mtf.Lowering(graph, {mesh: mesh_impl})
      actual_outputs = lowering.export_to_tf_tensor(mtf_outputs)
  
      tf_group = lowering.copy_masters_to_slices()
      init = tf.global_variables_initializer()
      self.evaluate(init)
      self.evaluate(tf_group)
      actual = self.evaluate(actual_outputs)
  
      self.assertEqual(actual.shape, (batch, heads, length_q, depth_v))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import mesh_tensorflow
  from mesh_tensorflow import test_utils
  import mock
  import numpy
  import tensorflow.compat.v1
  import tensorflow_probability
  from tensorflow.python.framework import test_util
label_desc: Use image node_id 9 for calling the LayersTest obj's underlying member method code with example usage: obj.testDotProductAttention(batch, heads, length_q, length_kv, depth_k, depth_v) without return types